摘要
基于移动窗口协方差估计和方差分量估计 ,提出了一种新的自适应Kalman滤波技术。计算结果证实 。
An adaptive filtering based on moving window covariance estimation is introduced after the shortcomings of covariance matrices formed by windowing residual vectors, innovation vectors and correction vectors of the dynamic states are analyzed. A new adaptive Kalman filter is developed by combining the moving window covariance and the variance component estimation. It shows that the new adaptive filtering is not only simple in calculation but also robust in controlling the measurement outliers and kinematic state disturbance.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2003年第6期714-718,共5页
Geomatics and Information Science of Wuhan University
基金
国家杰出青年基金资助项目 ( 4 982 5 10 7)
国家自然科学基金资助项目 ( 4 0 1740 0 9
40 2 740 0 2 )
关键词
移动开窗协方差估计
方差分量估计
自适应估计
抗差估计
moving window covariance estimation
adaptive estimation
robust estimation
variance components
